IDEAS home Printed from https://ideas.repec.org/p/boh/wpaper/06_2023.html
   My bibliography  Save this paper

European Insurance Market Analysis via a Joint Functional Clustering Method

Author

Listed:
  • Stavros Athanasiadis

    (Faculty of Economics, University of South Bohemia In České Budějovice)

Abstract

The enlargement of the European Union (EU) to include Central and South-Eastern European countries in 2004 and 2007 launched an integration process that unifies the economies and financial markets of member states and enables the convergence of these two areas. This study focuses on analyzing the development and similarity of the European insurance sector after the EU enlargement. We study 34 European insurance markets from 2004 until 2021 based on a certain set of indicators that characterize insurance markets, such as Insurance Density, Insurance Penetration and Gross Written Premiums to name a few. With a functional clustering method applied to such indicators, we try to reveal whether there are similarities between the individual countries that could explain the European insurance market homogeneity and convergence via the EU integration process. The proposed method has also a practical importance since it provides visualization of the clustering results through the construction of global envelopes. This study supports the works of EU policy makers that have a major impact on the ability of further integration of the European insurance market.

Suggested Citation

  • Stavros Athanasiadis, 2023. "European Insurance Market Analysis via a Joint Functional Clustering Method," Economics Working Papers 2023-06, University of South Bohemia in Ceske Budejovice, Faculty of Economics.
    • Handle: RePEc:boh:wpaper:06_2023
    as

    Download full text from publisher

    File URL: http://repec.ef.jcu.cz/RePEc/boh/wpaper/06_2023.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christian Hennig & Tim F. Liao, 2013. "How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(3), pages 309-369, May.
    2. in ’t Veld, Jan, 2019. "The economic benefits of the EU Single Market in goods and services," Journal of Policy Modeling, Elsevier, vol. 41(5), pages 803-818.
    3. Zhangyao Zhu & Na Liu & Wei Wang, 2021. "Early Warning of Financial Risk Based on K-Means Clustering Algorithm," Complexity, Hindawi, vol. 2021, pages 1-12, March.
    4. W. Jean Kwon & Leigh Wolfrom, 2016. "Analytical tools for the insurance market and macro-prudential surveillance," OECD Journal: Financial Market Trends, OECD Publishing, vol. 2016(1), pages 1-47.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Beckman, Jayson & Burfisher, Mary & Mitchell, Lorraine & Arita, Shawn, 2021. "Hidden obstacles to trade: The case of the EU’s Ban on beef hormones," Journal of Policy Modeling, Elsevier, vol. 43(6), pages 1332-1343.
    2. Elvira Pelle & Roberta Pappadà, 2021. "A clustering procedure for mixed-type data to explore ego network typologies: an application to elderly people living alone in Italy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1507-1533, December.
    3. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    4. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    5. Timini, Jacopo & Viani, Francesca, 2022. "A highway across the Atlantic? Trade and welfare effects of the EU-Mercosur agreement," International Economics, Elsevier, vol. 169(C), pages 291-308.
    6. Knut Blind & Florian Ramel & Charlotte Rochell, 2022. "The influence of standards and patents on long-term economic growth," The Journal of Technology Transfer, Springer, vol. 47(4), pages 979-999, August.
    7. Andrea Cerasa, 2016. "Combining homogeneous groups of preclassified observations with application to international trade," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(3), pages 229-259, August.
    8. Francesco Dotto & Alessio Farcomeni & Luis Angel García-Escudero & Agustín Mayo-Iscar, 2017. "A fuzzy approach to robust regression clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 691-710, December.
    9. Lenka PÅ™eÄ ková & Iveta PaleÄ ková, 2023. "Financial Stability of the Czech Insurance Companies," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 71(1), pages 65-86, January.
    10. Pietro Coretto & Christian Hennig, 2016. "Robust Improper Maximum Likelihood: Tuning, Computation, and a Comparison With Other Methods for Robust Gaussian Clustering," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1648-1659, October.
    11. Fritz Breuss, 2020. "25 Years of Austria's EU Membership. Quantifying the Economic Benefits With a DSGE Model," WIFO Working Papers 603, WIFO.
    12. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    13. Clara Dugord & Carine Franc, 2022. "Trajectories and individual determinants of regular cancer screening use over a long period based on data from the French E3N cohort," Post-Print hal-04385507, HAL.
    14. Efthymios Costa & Ioanna Papatsouma & Angelos Markos, 2023. "Benchmarking distance-based partitioning methods for mixed-type data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(3), pages 701-724, September.
    15. Nivorozhkin, Anton & Promberger, Markus, 2020. "Employment Subsidies for Long-Term Welfare Benefits Recipients: Reconciling Programmes Goals with Needs of Diverging Population Groups," IAB-Discussion Paper 202027, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    16. Natalia Zdanowska, 2023. "Socio-spatial Inequalities in a Context of "Great Economic Wealth". Case study of neighbourhoods of Luxembourg City," Papers 2307.09251, arXiv.org.
    17. Lauren Eyler & Alan Hubbard & Catherine Juillard, 2019. "Optimization and validation of the EconomicClusters model for facilitating global health disparities research: Examples from Cameroon and Ghana," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-22, May.
    18. Jonathon J. O’Brien & Michael T. Lawson & Devin K. Schweppe & Bahjat F. Qaqish, 2020. "Suboptimal Comparison of Partitions," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 435-461, July.
    19. Valerie D’Erman, 2021. "Competing Logics of Integration: EU Trade Post-Brexit," International Studies, , vol. 58(2), pages 219-233, April.
    20. Dugord, Clara & Franc, Carine, 2022. "Trajectories and individual determinants of regular cancer screening use over a long period based on data from the French E3N cohort," Social Science & Medicine, Elsevier, vol. 294(C).

    More about this item

    Keywords

    European insurance markets; enlargement EU; convergence; insurance integration; insurance market indicators; functional clustering; global rank envelope;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • F15 - International Economics - - Trade - - - Economic Integration
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boh:wpaper:06_2023. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Markéta Matějíčková (email available below). General contact details of provider: https://edirc.repec.org/data/efjcucz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.